Datasets:

colabfit
/

CuPd_CMS2019

configs:
  - config_name: default
    data_files: co/*.parquet
  - config_name: info
    data_files: ds.parquet
license: cc-by-4.0
tags:
  - molecular dynamics
  - mlip
  - interatomic potential
pretty_name: CuPd CMS2019

Cite this dataset
Gubaev, K., Podryabinkin, E. V., Hart, G. L., and Shapeev, A. V. CuPd CMS2019. ColabFit, 2023. https://doi.org/10.60732/1058e01c

This dataset has been curated and formatted for the ColabFit Exchange

This dataset is also available on the ColabFit Exchange:

https://materials.colabfit.org/id/DS_0ry6z1j8mi8c_0

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Dataset Name

CuPd CMS2019

Description

This dataset was generated using the following active learning scheme: 1) candidate structures were relaxed by a partially-trained MTP model, 2) structures for which the MTP had to perform extrapolation were passed to DFT to be re-computed, 3) the MTP was retrained, including the structures that were re-computed with DFT, 4) steps 1-3 were repeated until the MTP no longer extrapolated on any of the original candidate structures. The original candidate structures for this dataset included 40,000 unrelaxed configurations with BCC, FCC, and HCP lattices.

Dataset authors

Konstantin Gubaev, Evgeny V. Podryabinkin, Gus L.W. Hart, Alexander V. Shapeev

Publication

https://doi.org/10.1016/j.commatsci.2018.09.031

Original data link

https://gitlab.com/kgubaev/accelerating-high-throughput-searches-for-new-alloys-with-active-learning-data

License

CC-BY-4.0

Number of unique molecular configurations

522

Number of atoms

2450

Elements included

Cu, Pd

Properties included

energy, atomic forces, cauchy stress

Usage

ds.parquet : Aggregated dataset information.
co/ directory: Configuration rows each include a structure, calculated properties, and metadata.
cs/ directory : Configuration sets are subsets of configurations grouped by some common characteristic. If cs/ does not exist, no configurations sets have been defined for this dataset.
cs_co_map/ directory : The mapping of configurations to configuration sets (if defined).

Cite this dataset Gubaev, K., Podryabinkin, E. V., Hart, G. L., and Shapeev, A. V. CuPd CMS2019. ColabFit, 2023. https://doi.org/10.60732/1058e01c